> For the complete documentation index, see [llms.txt](https://docs.tonic.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.tonic.ai/app/generation/identify-sensitive-data.md).

# Identifying sensitive data

Tonic Structural uses its sensitivity scan to identify source data columns that contain sensitive information. The scan ignores truncated tables.

The sensitivity scan identifies Structural's built-in sensitivity types. It also looks for custom types that you define.

You can also manually mark a column as sensitive or not sensitive.

<table data-view="cards"><thead><tr><th></th><th></th><th></th><th data-hidden data-card-target data-type="content-ref"></th></tr></thead><tbody><tr><td><strong>Run the Structural sensitivity scan</strong></td><td>Run, configure, and get the results of the sensitivity scan.</td><td></td><td><a href="/app/generation/identify-sensitive-data/running-the-structural-sensitivity-scan.md">Running the Structural sensitivity scan</a></td></tr><tr><td><strong>Set column sensitivity manually</strong></td><td>Options to override the results of the sensitivity scan.</td><td></td><td><a href="/app/generation/identify-sensitive-data/sensitivity-set-manually.md">Manually indicating whether a column is sensitive</a></td></tr><tr><td><strong>Built-in sensitivity types</strong></td><td>Types of sensitive data that the sensitivity scan can identify.</td><td></td><td><a href="/app/generation/identify-sensitive-data/sensitivity-types-built-in.md">Built-in sensitivity types that Structural detects</a></td></tr><tr><td><strong>Configure custom sensitivity rules</strong></td><td>Set up rules to enable the scan to identify other sensitive columns based on the column data types and names.</td><td></td><td><a href="/app/generation/identify-sensitive-data/custom-sensitivity-rules.md">Creating and managing custom sensitivity rules</a></td></tr></tbody></table>


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation by asking a question.

Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:

```
GET https://docs.tonic.ai/app/generation/identify-sensitive-data.md?ask=<question>&goal=<user_goal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
